Methodological Deficits in Diagnostic Research Using ‘-Omics’ Technologies: Evaluation of the QUADOMICS Tool and Quality of Recently Published Studies

Background: QUADOMICS is an adaptation of QUADAS (a quality assessment tool for use in systematic reviews of diagnostic accuracy studies), which takes into account the particular challenges presented by '-omics' based technologies. Our primary objective was to evaluate the applicability and consistency of QUADOMICS. Subsequently we evaluated and describe the methodological quality of a sample of recently published studies using the tool. Methodology/Principal Findings: 45'-omics'- based diagnostic studies were identified by systematic search of Pubmed using suitable MeSH terms (>Genomics>, >Sensitivity and specificity>, >Diagnosis>). Three investigators independently assessed the quality of the articles using QUADOMICS and met to compare observations and generate a consensus. Consistency and applicability was assessed by comparing each reviewer's original rating with the consensus. Methodological quality was described using the consensus rating. Agreement was above 80% for all three reviewers. Four items presented difficulties with application, mostly due to the lack of a clearly defined gold standard. Methodological quality of our sample was poor; studies met roughly half of the applied criteria (mean ± sd, 54.7±18.4°%). Few studies were carried out in a population that mirrored the clinical situation in which the test would be used in practice, (6, 13.3%);none described patient recruitment sufficiently; and less than half described clinical and physiological factors that might influence the biomarker profile (20, 44.4%). Conclusions: The QUADOMICS tool can consistently be applied to diagnostic '-omics' studies presently published in biomedical journals. A substantial proportion of reports in this research field fail to address design issues that are fundamental to make inferences relevant for patient care. © 2010 Parker et al.This work was supported by the Spanish Agency for Health Technology Assessment, Exp PI06/90311, Instituto de Salud Carlos III and CIBER en Epidemiología y Salud Pública (CIBERESP) in SpainPeer Reviewe

Normalization in MALDI-TOF imaging datasets of proteins: practical considerations

Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial. In certain cases, however, these normalization algorithms may produce misleading results and possibly lead to wrong conclusions, e.g. regarding to potential biomarker distributions. This is typical for tissues in which signals of prominent abundance are present in confined areas, such as insulin in the pancreas or β-amyloid peptides in the brain. In this work, we investigated whether normalization can be improved if dominant signals are excluded from the calculation. Because manual interaction with the data (e.g., defining the abundant signals) is not desired for routine analysis, we investigated two alternatives: normalization on the spectra noise level or on the median of signal intensities in the spectrum. Normalization on the median and the noise level was found to be significantly more robust against artifact generation compared to normalization on the TIC. Therefore, we propose to include these normalization methods in the standard “toolbox” of MALDI imaging for reliable results under conditions of automation

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression

INTRODUCTION: Genomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution. METHODS: In the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed. RESULTS: We accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01). CONCLUSION: A major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions with fully invasive lesions, a much more heterogeneous group, clearly identified as the most importantly deregulated group of transcripts those encoding for various families of proteins in charge of extracellular matrix remodeling, invasion and cell motility functions

Microarray-Based Oncogenic Pathway Profiling in Advanced Serous Papillary Ovarian Carcinoma

Introduction: The identification of specific targets for treatment of ovarian cancer patients remains a challenge. The objective of this study is the analysis of oncogenic pathways in ovarian cancer and their relation with clinical outcome. Methodology: A meta-analysis of 6 gene expression datasets was done for oncogenic pathway activation scores: AKT, β-Catenin, BRCA, E2F1, EGFR, ER, HER2, INFα, INFγ, MYC, p53, p63, PI3K, PR, RAS, SRC, STAT3, TNFα, and TGFβ and VEGF-A. Advanced serous papillary tumours from uniformly treated patients were selected (N = 464) to find differences independent from stage-, histology- and treatment biases. Survival and correlations with documented prognostic signatures (wound healing response signature WHR/genomic grade index GGI/invasiveness gene signature IGS) were analysed. Results: The GGI, WHR, IGS score were unexpectedly increased in chemosensitive versus chemoresistant patients. PR and RAS activation scor

A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae)

The Colorado potato beetle is one of the most challenging agricultural pests to manage. It has shown a spectacular ability to adapt to a variety of solanaceaeous plants and variable climates during its global invasion, and, notably, to rapidly evolve insecticide resistance. To examine evidence of rapid evolutionary change, and to understand the genetic basis of herbivory and insecticide resistance, we tested for structural and functional genomic changes relative to other arthropod species using genome sequencing, transcriptomics, and community annotation. Two factors that might facilitate rapid evolutionary change include transposable elements, which comprise at least 17% of the genome and are rapidly evolving compared to other Coleoptera, and high levels of nucleotide diversity in rapidly growing pest populations. Adaptations to plant feeding are evident in gene expansions and differential expression of digestive enzymes in gut tissues, as well as expansions of gustatory receptors for bitter tasting. Surprisingly, the suite of genes involved in insecticide resistance is similar to other beetles. Finally, duplications in the RNAi pathway might explain why Leptinotarsa decemlineata has high sensitivity to dsRNA. The L. decemlineata genome provides opportunities to investigate a broad range of phenotypes and to develop sustainable methods to control this widely successful pest